Water quality assessment using remote sensing

Abstract

Water quality assessment is critical for environmental monitoring, public health, and sustainable resource management. Traditional methods of water quality monitoring, though accurate, are often time-consuming, labour-intensive, and limited in spatial coverage. Remote sensing technology has emerged as a powerful tool to overcome these limitations, enabling large-scale, cost-effective, and real-time monitoring of water bodies. This study explores the application of remote sensing techniques for assessing key water quality parameters, such as chlorophyll-a concentration, turbidity, total suspended solids (TSS), and dissolved organic matter (DOM). By leveraging multispectral and hyperspectral satellite imagery, as well as advanced algorithms and machine learning models, remote sensing provides valuable insights into spatial and temporal variations in water quality. The integration of remote sensing data with ground-based measurements enhances the accuracy and reliability of assessments, facilitating early detection of pollution events and supporting decision-making for water resource management. This paper reviews recent advancements, challenges, and future prospects of remote sensing in water quality assessment, highlighting its potential to address global water quality issues in an era of increasing environmental change.